2025
Journal article
Restricted
Transverse and axial vibrations of masonry beams and towers
Girardi M.
Studying the effects of the earthquakes’ vertical component on the dynamic response of masonry buildings is still an open issue. This subject is investigated using a simplified masonry-like beam model with a generalized stress–strain relationship. The nonlinear dynamic equations that couple the transverse and axial oscillations of the beam are solved numerically. Some examples are presented and discussed, focusing on the structural typology of masonry towers and the recent earthquakes that threatened the North-Central Apennines in Italy.Source: INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, vol. 175
DOI: 10.1016/j.ijnonlinmec.2025.105086
Metrics:
Girardi M.
Studying the effects of the earthquakes’ vertical component on the dynamic response of masonry buildings is still an open issue. This subject is investigated using a simplified masonry-like beam model with a generalized stress–strain relationship. The nonlinear dynamic equations that couple the transverse and axial oscillations of the beam are solved numerically. Some examples are presented and discussed, focusing on the structural typology of masonry towers and the recent earthquakes that threatened the North-Central Apennines in Italy.Source: INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, vol. 175
DOI: 10.1016/j.ijnonlinmec.2025.105086
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International Journal of Non-Linear Mechanics 
| CNR IRIS | CNR IRIS | CNR IRIS | www.sciencedirect.com
2025
Journal article
Open Access
Structural monitoring of heritage buildings via deep learning algorithms
Girardi M., Gurioli G., Messina N.
Monitoring systems constitute a significant, non-invasive tool for verifying the structural health of buildings and infrastructure over time. Deep learning neural networks can be used to analyse data from long-term monitoring systems, such as time series of velocity/acceleration measured at specific points and environmental parameters, and to predict the main features of the buildings’ structural behaviour with respect to ambient stresses. Potential anomalies of the structure’s vibrational features related to damage or unexpected events, such as earthquakes or exceptional loads, can also be detected. The paper focuses on the application of a Temporal Fusion Transformer (TFT) network to data from the dynamic monitoring of a medieval tower in the historic centre of Lucca (Tuscany, Italy).Source: ERCIM NEWS, vol. 141, pp. 13-14
Girardi M., Gurioli G., Messina N.
Monitoring systems constitute a significant, non-invasive tool for verifying the structural health of buildings and infrastructure over time. Deep learning neural networks can be used to analyse data from long-term monitoring systems, such as time series of velocity/acceleration measured at specific points and environmental parameters, and to predict the main features of the buildings’ structural behaviour with respect to ambient stresses. Potential anomalies of the structure’s vibrational features related to damage or unexpected events, such as earthquakes or exceptional loads, can also be detected. The paper focuses on the application of a Temporal Fusion Transformer (TFT) network to data from the dynamic monitoring of a medieval tower in the historic centre of Lucca (Tuscany, Italy).Source: ERCIM NEWS, vol. 141, pp. 13-14
See at:
ercim-news.ercim.eu 
| CNR IRIS | CNR IRIS
2025
Contribution to book
Restricted
Applications and open issues in the structural health monitoring of historic buildings
Maria Girardi, Cristina Padovani, Daniele Pellegrini
This chapter describes the main features and components of the Structural Health Monitoring of historic buildings, including experimental campaigns (in which dynamic and environmental data are recorded), data processing, anomaly detection and finite element nonlinear simulations. The results of the dynamic monitoring campaigns conducted on three masonry towers in the historic centre of Lucca from 2015 to 2022 are then presented. The vibrations of the San Frediano bell tower, the Clock Tower and the Guinigi Tower were continuously monitored: high–sensitivity seismic stations were installed on the structures to record their response to the dynamic actions of the surrounding environment. The effects of natural and anthropic vibration sources on the dynamic behaviour of the towers were also investigated to detect novelties and anomalies that occurred during the monitoring period.Source: SPRINGER INDAM SERIES, vol. 65, pp. 151-172
DOI: 10.1007/978-981-96-4550-3_10
Metrics:
Maria Girardi, Cristina Padovani, Daniele Pellegrini
This chapter describes the main features and components of the Structural Health Monitoring of historic buildings, including experimental campaigns (in which dynamic and environmental data are recorded), data processing, anomaly detection and finite element nonlinear simulations. The results of the dynamic monitoring campaigns conducted on three masonry towers in the historic centre of Lucca from 2015 to 2022 are then presented. The vibrations of the San Frediano bell tower, the Clock Tower and the Guinigi Tower were continuously monitored: high–sensitivity seismic stations were installed on the structures to record their response to the dynamic actions of the surrounding environment. The effects of natural and anthropic vibration sources on the dynamic behaviour of the towers were also investigated to detect novelties and anomalies that occurred during the monitoring period.Source: SPRINGER INDAM SERIES, vol. 65, pp. 151-172
DOI: 10.1007/978-981-96-4550-3_10
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CNR IRIS | CNR IRIS | CNR IRIS | link.springer.com
2025
Journal article
Open Access
Regularization in structural model updating in the presence of noisy data
Girardi M., Padovani C., Pellegrini D., Robol L.
This article addresses the presence of noise when solving the inverse problem of determining the material properties of an elastic engineering structure from measured vibration data. After identifying the frequencies, material properties are determined by solving an optimization problem. However, if the experimental frequencies are affected by noise (as often happens in practice), this can lead to inaccuracy due to the ill-conditioning of the problem. A regularization strategy based on Tikhonov regularization is discussed, and an automatic regularization parameter choice is introduced to deal with cases where the noise level is not known beforehand. The algorithm is tested on three examples, including artificial models where the exact solution is known and a case study from the Matilde donjon in Livorno, with experimental data measured by seismic stations during ambient vibration tests. The proposed method consistently performs well across all tests, validating the reliability of the approach.Source: INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, vol. 126 (issue 17)
DOI: 10.1002/nme.70113
Project(s): PiattafoRma open-sourcE orientata ai digital twins: tecniche di digitalizzazione 3D, monitoraggio delle Vibrazioni e mOdellazione agli eLementi finiti per la valUTazione dello stato di conservazIone di edifici stOrici e iNfrastrutture civili
Metrics:
Girardi M., Padovani C., Pellegrini D., Robol L.
This article addresses the presence of noise when solving the inverse problem of determining the material properties of an elastic engineering structure from measured vibration data. After identifying the frequencies, material properties are determined by solving an optimization problem. However, if the experimental frequencies are affected by noise (as often happens in practice), this can lead to inaccuracy due to the ill-conditioning of the problem. A regularization strategy based on Tikhonov regularization is discussed, and an automatic regularization parameter choice is introduced to deal with cases where the noise level is not known beforehand. The algorithm is tested on three examples, including artificial models where the exact solution is known and a case study from the Matilde donjon in Livorno, with experimental data measured by seismic stations during ambient vibration tests. The proposed method consistently performs well across all tests, validating the reliability of the approach.Source: INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, vol. 126 (issue 17)
DOI: 10.1002/nme.70113
Project(s): PiattafoRma open-sourcE orientata ai digital twins: tecniche di digitalizzazione 3D, monitoraggio delle Vibrazioni e mOdellazione agli eLementi finiti per la valUTazione dello stato di conservazIone di edifici stOrici e iNfrastrutture civili
Metrics:
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CNR IRIS | onlinelibrary.wiley.com | CNR IRIS
2025
Conference article
Open Access
Using Artificial Intelligence for the dynamic monitoring of an old tower in the Medicean Port of Livorno (Italy)
Bartoli G., Betti M., Girardi M., Gurioli G., Messina N., Padovani C., Pellegrini D., Zini G.
This paper applies deep learning techniques to the signals acquired during a long-term dynamic monitoring campaign conducted on the Matilde donjon, a fortified keep belonging to the Old Fortress in the Medicean Port of Livorno, Italy. The time series collected during the dynamic monitoring complemented with the environmental parameters (temperature, wind speed) were used to train a deep learning neural network and forecast the dynamical behaviour of the tower. Although the signals are sparse and noisy, the algorithm can learn the main features of the tower’s dynamic response and detect anomalies and events occurring in the surrounding environment.Source: LECTURE NOTES IN CIVIL ENGINEERING, vol. 676, pp. 54-62. Porto, Portugal, 2-4/07/2025
DOI: 10.1007/978-3-031-96114-4_7
Metrics:
Bartoli G., Betti M., Girardi M., Gurioli G., Messina N., Padovani C., Pellegrini D., Zini G.
This paper applies deep learning techniques to the signals acquired during a long-term dynamic monitoring campaign conducted on the Matilde donjon, a fortified keep belonging to the Old Fortress in the Medicean Port of Livorno, Italy. The time series collected during the dynamic monitoring complemented with the environmental parameters (temperature, wind speed) were used to train a deep learning neural network and forecast the dynamical behaviour of the tower. Although the signals are sparse and noisy, the algorithm can learn the main features of the tower’s dynamic response and detect anomalies and events occurring in the surrounding environment.Source: LECTURE NOTES IN CIVIL ENGINEERING, vol. 676, pp. 54-62. Porto, Portugal, 2-4/07/2025
DOI: 10.1007/978-3-031-96114-4_7
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CNR IRIS | link.springer.com | CNR IRIS | CNR IRIS
2024
Journal article
Open Access
Deep learning and structural health monitoring: temporal fusion transformers for anomaly detection in masonry towers
Falchi F., Girardi M., Gurioli G., Messina N., Padovani C., Pellegrini D.
Detecting anomalies in the vibrational features of age-old buildings is crucial within the Structural Health Monitoring (SHM) framework. The SHM techniques can leverage information from onsite measurements and environmental sources to identify the dynamic properties (such as the frequencies) of the monitored structure, searching for possible deviations or unusual behavior over time. In this paper, the Temporal Fusion Transformer (TFT) network, a deep learning algorithm initially designed for multi-horizon time series forecasting and tested on electricity, traffic, retail, and volatility problems, is applied to SHM. The TFT approach is adopted to investigate the behavior of the Guinigi Tower located in Lucca (Italy) and subjected to a long-term dynamic monitoring campaign. The TFT network is trained on the tower's experimental frequencies enriched with other environmental parameters. The transformer is then employed to predict the vibrational features (natural frequencies, root mean squares values of the velocity time series) and detect possible anomalies or unexpected events by inspecting how much the actual frequencies deviate from the predicted ones. The TFT technique is used to detect the effects of the Viareggio earthquake that occurred on 6 February 2022, and the structural damage induced by three simulated damage scenarios.Source: MECHANICAL SYSTEMS AND SIGNAL PROCESSING, vol. 215 (issue 111382)
DOI: 10.1016/j.ymssp.2024.111382
Metrics:
Falchi F., Girardi M., Gurioli G., Messina N., Padovani C., Pellegrini D.
Detecting anomalies in the vibrational features of age-old buildings is crucial within the Structural Health Monitoring (SHM) framework. The SHM techniques can leverage information from onsite measurements and environmental sources to identify the dynamic properties (such as the frequencies) of the monitored structure, searching for possible deviations or unusual behavior over time. In this paper, the Temporal Fusion Transformer (TFT) network, a deep learning algorithm initially designed for multi-horizon time series forecasting and tested on electricity, traffic, retail, and volatility problems, is applied to SHM. The TFT approach is adopted to investigate the behavior of the Guinigi Tower located in Lucca (Italy) and subjected to a long-term dynamic monitoring campaign. The TFT network is trained on the tower's experimental frequencies enriched with other environmental parameters. The transformer is then employed to predict the vibrational features (natural frequencies, root mean squares values of the velocity time series) and detect possible anomalies or unexpected events by inspecting how much the actual frequencies deviate from the predicted ones. The TFT technique is used to detect the effects of the Viareggio earthquake that occurred on 6 February 2022, and the structural damage induced by three simulated damage scenarios.Source: MECHANICAL SYSTEMS AND SIGNAL PROCESSING, vol. 215 (issue 111382)
DOI: 10.1016/j.ymssp.2024.111382
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CNR IRIS | ISTI Repository | www.sciencedirect.com | CNR IRIS | CNR IRIS
2024
Journal article
Open Access
Seismic response and ambient vibrations of a Mediaeval Tower in the Mugello area (Italy)
R. M. Azzara, V. Cardinali, M. Girardi, C. Padovani, D. Pellegrini, M. Tanganelli
This paper describes the experimental campaigns on the Tower of the Palazzo dei Vicari in Scarperia, a village in the Mugello area (Tuscany) exposed to high seismic hazards. The first campaign was carried out from December 2019 to January 2020, and the Tower underwent the so-called Mugello seismic sequence, which featured an M 4.5 earthquake. Other ambient vibration tests were repeated in June 2021 and September 2023 when another seismic sequence struck the area near Scarperia. These tests aimed to characterise the Tower’s dynamic behaviour under ambient and seismic excitations and check the response of the Tower over time. The experimental results were then used to calibrate a finite-element model of the Tower and estimate its seismic vulnerability. Several numerical simulations were conducted on the calibrated model using the NOSA-ITACA code for nonlinear structural analysis of masonry buildings. The dynamic behaviour of the Tower subjected to a seismic sequence recorded in 2023 by a seismic station at the base was investigated by comparing the velocities recorded along the Tower’s height with their numerical counterparts. Furthermore, several pushover analyses were conducted to investigate the collapse of the Tower as the load’s distribution and direction varied.Source: JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
DOI: 10.1007/s13349-024-00824-7
Project(s): PiattafoRma open-sourcE orientata ai digital twins: tecniche di digitalizzazione 3D, monitoraggio delle Vibrazioni e mOdellazione agli eLementi finiti per la valUTazione dello stato di conservazIone di edifici stOrici e iNfrastrutture civili
Metrics:
R. M. Azzara, V. Cardinali, M. Girardi, C. Padovani, D. Pellegrini, M. Tanganelli
This paper describes the experimental campaigns on the Tower of the Palazzo dei Vicari in Scarperia, a village in the Mugello area (Tuscany) exposed to high seismic hazards. The first campaign was carried out from December 2019 to January 2020, and the Tower underwent the so-called Mugello seismic sequence, which featured an M 4.5 earthquake. Other ambient vibration tests were repeated in June 2021 and September 2023 when another seismic sequence struck the area near Scarperia. These tests aimed to characterise the Tower’s dynamic behaviour under ambient and seismic excitations and check the response of the Tower over time. The experimental results were then used to calibrate a finite-element model of the Tower and estimate its seismic vulnerability. Several numerical simulations were conducted on the calibrated model using the NOSA-ITACA code for nonlinear structural analysis of masonry buildings. The dynamic behaviour of the Tower subjected to a seismic sequence recorded in 2023 by a seismic station at the base was investigated by comparing the velocities recorded along the Tower’s height with their numerical counterparts. Furthermore, several pushover analyses were conducted to investigate the collapse of the Tower as the load’s distribution and direction varied.Source: JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
DOI: 10.1007/s13349-024-00824-7
Project(s): PiattafoRma open-sourcE orientata ai digital twins: tecniche di digitalizzazione 3D, monitoraggio delle Vibrazioni e mOdellazione agli eLementi finiti per la valUTazione dello stato di conservazIone di edifici stOrici e iNfrastrutture civili
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Journal of Civil Structural Health Monitoring | IRIS Cnr | IRIS Cnr | CNR IRIS
2024
Conference article
Open Access
Vibration monitoring of historical towers: new contributions from data science
Girardi M., Gurioli G., Messina N., Padovani C., Pellegrini D.
Deep neural networks are used to study the ambient vibrations of the medieval towers of the San Frediano Cathedral and the Guinigi Palace in the historic centre of Lucca. The towers have been continuously monitored for many months via high-sensitivity seismic stations. The recorded data sets integrated with environmental parameters are employed to train a Temporal Fusion Transformer network and forecast the dynamic behaviour of the monitored structures. The results show that the adopted algorithm can learn the main features of the towers’ dynamic response, predict its evolution over time, and detect anomalies.Source: LECTURE NOTES IN CIVIL ENGINEERING, vol. 514, pp. 15-24. Naples, Italy, 21-24/05/2024
DOI: 10.1007/978-3-031-61421-7_2
Metrics:
Girardi M., Gurioli G., Messina N., Padovani C., Pellegrini D.
Deep neural networks are used to study the ambient vibrations of the medieval towers of the San Frediano Cathedral and the Guinigi Palace in the historic centre of Lucca. The towers have been continuously monitored for many months via high-sensitivity seismic stations. The recorded data sets integrated with environmental parameters are employed to train a Temporal Fusion Transformer network and forecast the dynamic behaviour of the monitored structures. The results show that the adopted algorithm can learn the main features of the towers’ dynamic response, predict its evolution over time, and detect anomalies.Source: LECTURE NOTES IN CIVIL ENGINEERING, vol. 514, pp. 15-24. Naples, Italy, 21-24/05/2024
DOI: 10.1007/978-3-031-61421-7_2
Metrics:
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IRIS Cnr | IRIS Cnr | IRIS Cnr | doi.org | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
Leveraging advanced numerical calibration to filter out temperature effects on vibration-based monitoring data: application to the Mogadouro clock tower
Barontini A., Pellegrini D., Testa F., Girardi M., Masciotta M., Mendes N., Padovani C.
This study investigates the advantages of integrating physics knowledge to enhance traditional data-driven methods for damage detection and early warning in a monitored structure. The implemented method combines the ability to predict variations in modal properties (such as natural frequencies) under changing temperatures, using a highly reliable Finite Element (FE) model calibrated to the experimental response of the structure, with a robust anomaly detection strategy to process new monitoring data and classify it as damaged or undamaged. The relationship between temperature and modal properties, as evaluated through the FE model, is used to normalise the monitoring data. This process filters out the effects of the environmental variation, potentially magnifying the effects of damage, which are then investigated through machine learning algorithms for classification purpose. The procedure is validated by analysing a real case study, the Mogadouro clock tower in Portugal. Several scenarios of available knowledge during the training of the damage detection strategy are simulated, discussing advantages and identifying areas for future improvement.DOI: 10.23967/eccomas.2024.247
Metrics:
Barontini A., Pellegrini D., Testa F., Girardi M., Masciotta M., Mendes N., Padovani C.
This study investigates the advantages of integrating physics knowledge to enhance traditional data-driven methods for damage detection and early warning in a monitored structure. The implemented method combines the ability to predict variations in modal properties (such as natural frequencies) under changing temperatures, using a highly reliable Finite Element (FE) model calibrated to the experimental response of the structure, with a robust anomaly detection strategy to process new monitoring data and classify it as damaged or undamaged. The relationship between temperature and modal properties, as evaluated through the FE model, is used to normalise the monitoring data. This process filters out the effects of the environmental variation, potentially magnifying the effects of damage, which are then investigated through machine learning algorithms for classification purpose. The procedure is validated by analysing a real case study, the Mogadouro clock tower in Portugal. Several scenarios of available knowledge during the training of the damage detection strategy are simulated, discussing advantages and identifying areas for future improvement.DOI: 10.23967/eccomas.2024.247
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CNR IRIS | www.scipedia.com | CNR IRIS
2023
Journal article
Open Access
Dynamic Behaviour of the Carillon Tower in Castel San Pietro Terme, Italy
Azzara Rm, Girardi M, Padovani C, Pellegrini D
This paper presents the experimental investigations conducted on the carillon tower of the Santissimo Crocifsso Sanctuary in Castel San Pietro (Bologna, Italy) and the analysis of data collected by using velocimeters and accelerometers installed on the structure. The main goal is to assess the effects of the swinging bells on the dynamic behaviour of the tower. The paper's novelty relies on the kind of structure monitored and the originality of the experiments. The structure is a rare example of a carillon tower, with fifty-five bells of different sizes, subjected to a careful measurement campaign never carried out before. Six experiments were conducted selectively by activating the bells to measure the tower's response induced by different vibration sources and determine the peak velocities recorded by using instruments at different heights. Two ambient vibration tests complemented the six experiments. The carillon's action induces low velocities on the tower, while experiments involving the bells swinging in the upper chamber produce the highest velocity values in the swinging direction; these values are more significant than those induced by the carillon alone. The most robust action is induced on the tower when all the bells (carillon plus swinging bells) ring. The experimental results are complemented by numerical simulations of the dynamic behaviour of the tower subjected to the action of a swinging bell.Source: STRUCTURAL CONTROL AND HEALTH MONITORING
DOI: 10.1155/2023/1045234
Metrics:
Azzara Rm, Girardi M, Padovani C, Pellegrini D
This paper presents the experimental investigations conducted on the carillon tower of the Santissimo Crocifsso Sanctuary in Castel San Pietro (Bologna, Italy) and the analysis of data collected by using velocimeters and accelerometers installed on the structure. The main goal is to assess the effects of the swinging bells on the dynamic behaviour of the tower. The paper's novelty relies on the kind of structure monitored and the originality of the experiments. The structure is a rare example of a carillon tower, with fifty-five bells of different sizes, subjected to a careful measurement campaign never carried out before. Six experiments were conducted selectively by activating the bells to measure the tower's response induced by different vibration sources and determine the peak velocities recorded by using instruments at different heights. Two ambient vibration tests complemented the six experiments. The carillon's action induces low velocities on the tower, while experiments involving the bells swinging in the upper chamber produce the highest velocity values in the swinging direction; these values are more significant than those induced by the carillon alone. The most robust action is induced on the tower when all the bells (carillon plus swinging bells) ring. The experimental results are complemented by numerical simulations of the dynamic behaviour of the tower subjected to the action of a swinging bell.Source: STRUCTURAL CONTROL AND HEALTH MONITORING
DOI: 10.1155/2023/1045234
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CNR IRIS | onlinelibrary.wiley.com | ISTI Repository | CNR IRIS
2023
Other
Unknown
Analisi del collasso di strutture ad arco in muratura: indagini sperimentali su modelli in scala
E. Casassa, (relatori: Barsotti R., Barsi F., Girardi M., Padovani C., Bennati S. )
La tesi vuole analizzare il comportamento sperimentale di modelli in scala di arco sottoposti a carichi pseudostatici incrementali. I modelli degli archi sono ottenuti accostando, a secco, i conci ottenuti attraverso una stampante 3D. L'azione sismica viene simulata come una forza statica d'inerzia, proporzionale alla massa. In questo senso, per applicare un pattern di carichi adeguato è stata prevista la costruzione di una tilting table. I risultati sperimentali, raccolti sottoforma di moltiplicatori dei carichi orizzontali di collasso , vengono successivamente analizzati criticamente confrontandoli con i risultati teorici (trovati attraverso il teorema cinematico) ed i risultati forniti dal software di calcolo NOSA-ITACA.
E. Casassa, (relatori: Barsotti R., Barsi F., Girardi M., Padovani C., Bennati S. )
La tesi vuole analizzare il comportamento sperimentale di modelli in scala di arco sottoposti a carichi pseudostatici incrementali. I modelli degli archi sono ottenuti accostando, a secco, i conci ottenuti attraverso una stampante 3D. L'azione sismica viene simulata come una forza statica d'inerzia, proporzionale alla massa. In questo senso, per applicare un pattern di carichi adeguato è stata prevista la costruzione di una tilting table. I risultati sperimentali, raccolti sottoforma di moltiplicatori dei carichi orizzontali di collasso , vengono successivamente analizzati criticamente confrontandoli con i risultati teorici (trovati attraverso il teorema cinematico) ed i risultati forniti dal software di calcolo NOSA-ITACA.
See at: CNR ExploRA
2023
Other
Restricted
Monitoraggio dinamico di ponti mediante reti wireless di sensori
Marra Am, Morano G, Nicese B, Salvatori L, Spinelli P, Girardi M, Padovani C, Pellegrini D
Report finale del progetto "Monitoraggio dinamico di ponti mediante reti wireless di sensori" (MOODWISE).
Marra Am, Morano G, Nicese B, Salvatori L, Spinelli P, Girardi M, Padovani C, Pellegrini D
Report finale del progetto "Monitoraggio dinamico di ponti mediante reti wireless di sensori" (MOODWISE).
2023
Other
Restricted
Progetto REVOLUTION - Piattaforma open-source orientata ai digital twins: tecniche di digitalizzazione 3D, monitoraggio delle vibrazioni e modellazione agli elementi finiti per la valutazione dello stato di conservazione di edifici storici e infrastrutture civili
Pellegrini D, Girardi M, Gurioli G, Padovani C
Report tecnico scientifico n.1 (attività svolta nel periodo 15 febbarioi 2022 - 15 febbraio 2023).
Pellegrini D, Girardi M, Gurioli G, Padovani C
Report tecnico scientifico n.1 (attività svolta nel periodo 15 febbarioi 2022 - 15 febbraio 2023).
2023
Journal article
Open Access
Experimental investigations and numerical modelling: a fruitful interaction for the nonlinear dynamical analysis of masonry structures
Azzara R. M., Girardi M., Padovani C., Pellegrini D.
This paper describes the experiments carried out on a medieval masonry tower in the historic centre of Lucca and some finite element numerical simulations of the tower's experimental response. The Guinigi Tower, one of the most iconic monuments in Lucca, has been continuously monitored by high-sensitive seismic stations that recorded the structure's response to the dynamic actions of the surrounding environment. The monitoring campaign results have been analysed to show the effectiveness of dynamic monitoring as a valuable source of information on the structural properties of the tower. The dynamic analyses of the tower and the surrounding palace subjected to some seismic events recorded during the experiments have highlighted the capabilities of experiment-based finite element modelling. The calibration of the finite element model and the numerical analysis have been carried out by resorting to procedures developed at ISTI-CNR and able to consider the nonlinear behaviour of masonry materials.Source: CONTINUUM MECHANICS AND THERMODYNAMICS
DOI: 10.1007/s00161-023-01264-2
Metrics:
Azzara R. M., Girardi M., Padovani C., Pellegrini D.
This paper describes the experiments carried out on a medieval masonry tower in the historic centre of Lucca and some finite element numerical simulations of the tower's experimental response. The Guinigi Tower, one of the most iconic monuments in Lucca, has been continuously monitored by high-sensitive seismic stations that recorded the structure's response to the dynamic actions of the surrounding environment. The monitoring campaign results have been analysed to show the effectiveness of dynamic monitoring as a valuable source of information on the structural properties of the tower. The dynamic analyses of the tower and the surrounding palace subjected to some seismic events recorded during the experiments have highlighted the capabilities of experiment-based finite element modelling. The calibration of the finite element model and the numerical analysis have been carried out by resorting to procedures developed at ISTI-CNR and able to consider the nonlinear behaviour of masonry materials.Source: CONTINUUM MECHANICS AND THERMODYNAMICS
DOI: 10.1007/s00161-023-01264-2
Metrics:
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CNR IRIS | link.springer.com | ISTI Repository | CNR IRIS
2023
Journal article
Open Access
Effects of temperature variations on the modal properties of masonry structures: an experimental-based numerical modelling approach
Pellegrini D., Barontini A., Girardi M., Lourenço P. B., Masciotta M. G., Mendes N., Padovani C., Ramos L. F.
Long-term ambient vibration monitoring campaigns show that environmental parameters (such as temperature, humidity, wind speed and direction) can influence the structures' static and dynamic behaviour. In particular, thermal variations can affect the modal characteristics of ancient masonry constructions. This work presents a procedure combining experimental and numerical steps to monitor, assess and model the dynamic behaviour of masonry structures subjected to thermal loads. The procedure is tested and validated through two numerical examples and the simulation of a full-scale masonry structure, the Mogadouro clock tower in Portugal, monitored with accelerometers and temperature and humidity sensors.Source: STRUCTURES, vol. 53, pp. 595-613
DOI: 10.1016/j.istruc.2023.04.080
Metrics:
Pellegrini D., Barontini A., Girardi M., Lourenço P. B., Masciotta M. G., Mendes N., Padovani C., Ramos L. F.
Long-term ambient vibration monitoring campaigns show that environmental parameters (such as temperature, humidity, wind speed and direction) can influence the structures' static and dynamic behaviour. In particular, thermal variations can affect the modal characteristics of ancient masonry constructions. This work presents a procedure combining experimental and numerical steps to monitor, assess and model the dynamic behaviour of masonry structures subjected to thermal loads. The procedure is tested and validated through two numerical examples and the simulation of a full-scale masonry structure, the Mogadouro clock tower in Portugal, monitored with accelerometers and temperature and humidity sensors.Source: STRUCTURES, vol. 53, pp. 595-613
DOI: 10.1016/j.istruc.2023.04.080
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CNR IRIS | www.sciencedirect.com | CNR IRIS | CNR IRIS
2023
Conference article
Open Access
Long-term monitoring of a masonry tower with wireless accelerometers
Zini G., Marafini F., Monchetti S., Betti M., Facchini L., Bartoli G., Girardi M., Gurioli G., Padovani C., Pellegrini D.
During the last decades, significant efforts have been made to define appropriate Structural Health Monitoring (SHM) frameworks based on the vibration signatures collected by accelerometers. Data-driven approaches are increasingly adopted for damage detection through the identification of anomalies in the distribution of the frequencies. This paper analyzes the long-term monitoring data acquired from a system installed on the Matilde tower in Livorno (Italy). The tower is a historic masonry structure monitored since the end of 2018 using a wireless sensor network developed during the MOSCARDO project.
Zini G., Marafini F., Monchetti S., Betti M., Facchini L., Bartoli G., Girardi M., Gurioli G., Padovani C., Pellegrini D.
During the last decades, significant efforts have been made to define appropriate Structural Health Monitoring (SHM) frameworks based on the vibration signatures collected by accelerometers. Data-driven approaches are increasingly adopted for damage detection through the identification of anomalies in the distribution of the frequencies. This paper analyzes the long-term monitoring data acquired from a system installed on the Matilde tower in Livorno (Italy). The tower is a historic masonry structure monitored since the end of 2018 using a wireless sensor network developed during the MOSCARDO project.
See at:
2023.compdyn.org | CNR IRIS | ISTI Repository | CNR IRIS
2023
Contribution to book
Open Access
Numerical modelling of historical masonry structures with the finite element code NOSA-ITACA
Girardi M., Padovani C., Pellegrini D., Porcelli M., Robol L.
This chapter presents the finite element code NOSA-ITACA for static and modal analyses of masonry structures of architectural interest. NOSA-ITACA adopts the constitutive equation of masonrylike materials, which considers masonry a non-linear elastic material with zero tensile strength. The capability of modelling restoration and consolidation operations makes the code a helpful tool for maintaining historical buildings. In recent years, long-term vibration monitoring turned out to be an effective non-destructive technique to investigate the dynamic behaviour and check the health status of historical buildings. Changes in their dynamic properties, such as natural frequencies, can represent effective damage indicators. The latest NOSA-ITACA developments are oriented towards structural health monitoring. The availability of the experimental modal properties of a structure makes it possible to calibrate its finite element model via model updating procedures. In particular, the unknown structure's characteristics, such as materials' properties and boundary conditions, can be determined by solving a minimum problem whose objective function is expressed as the discrepancy between experimental frequencies and mode shapes and their numerical counterparts. Several case studies are presented to show the main features of NOSA-ITACA and its effectiveness in the conservation of architectural heritage.Source: SPRINGER INDAM SERIES (ONLINE), vol. 55, pp. 133-152
DOI: 10.1007/978-981-99-3679-3_9
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Girardi M., Padovani C., Pellegrini D., Porcelli M., Robol L.
This chapter presents the finite element code NOSA-ITACA for static and modal analyses of masonry structures of architectural interest. NOSA-ITACA adopts the constitutive equation of masonrylike materials, which considers masonry a non-linear elastic material with zero tensile strength. The capability of modelling restoration and consolidation operations makes the code a helpful tool for maintaining historical buildings. In recent years, long-term vibration monitoring turned out to be an effective non-destructive technique to investigate the dynamic behaviour and check the health status of historical buildings. Changes in their dynamic properties, such as natural frequencies, can represent effective damage indicators. The latest NOSA-ITACA developments are oriented towards structural health monitoring. The availability of the experimental modal properties of a structure makes it possible to calibrate its finite element model via model updating procedures. In particular, the unknown structure's characteristics, such as materials' properties and boundary conditions, can be determined by solving a minimum problem whose objective function is expressed as the discrepancy between experimental frequencies and mode shapes and their numerical counterparts. Several case studies are presented to show the main features of NOSA-ITACA and its effectiveness in the conservation of architectural heritage.Source: SPRINGER INDAM SERIES (ONLINE), vol. 55, pp. 133-152
DOI: 10.1007/978-981-99-3679-3_9
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2023
Conference article
Open Access
Towards a cloud-based platform for structural health monitoring: implementation and numerical issues
Croce T, Girardi M, Gurioli G, Padovani C, Pellegrini D
Structural Health Monitoring (SHM) is increasingly important in protecting and maintaining architectural heritage. Its main goal is to distinguish ordinary fluctuations in a building's response from other, possibly anomalous, behaviour. SHM starts setting sensors to measure accelerations or velocities and other environmental parameters over time at fixed points of the structure. The time series processing makes it possible to perform modal tracking and damage/anomaly detection while correlating dynamical and environmental parameters. In practice, these activities are conducted separately, using different numerical codes. Thus, the idea is to take the first step to distance from such practice, leveraging the MOSCARDO system, which encompasses a Wireless Sensor Network (WSN) and a platform designed according to a cloud architecture that provides services for storing and processing data from the WSN. We employ a code based on the Stochastic Subspace Identification (SSI) technique to improve the system's capabilities, and we exploit the SSI's theoretical features to get an efficient implementation that will be integrated into the cloud-based platform. This pipeline is here presented considering data collected from a monitoring campaign on the "Matilde donjon" in Livorno (Italy) and reporting preliminary numerical results on the identification of the modal parameters.Source: LECTURE NOTES IN CIVIL ENGINEERING, pp. 610-619. Milano, Italy, 30-08/01-09/2023
DOI: 10.1007/978-3-031-39109-5_62
Metrics:
Croce T, Girardi M, Gurioli G, Padovani C, Pellegrini D
Structural Health Monitoring (SHM) is increasingly important in protecting and maintaining architectural heritage. Its main goal is to distinguish ordinary fluctuations in a building's response from other, possibly anomalous, behaviour. SHM starts setting sensors to measure accelerations or velocities and other environmental parameters over time at fixed points of the structure. The time series processing makes it possible to perform modal tracking and damage/anomaly detection while correlating dynamical and environmental parameters. In practice, these activities are conducted separately, using different numerical codes. Thus, the idea is to take the first step to distance from such practice, leveraging the MOSCARDO system, which encompasses a Wireless Sensor Network (WSN) and a platform designed according to a cloud architecture that provides services for storing and processing data from the WSN. We employ a code based on the Stochastic Subspace Identification (SSI) technique to improve the system's capabilities, and we exploit the SSI's theoretical features to get an efficient implementation that will be integrated into the cloud-based platform. This pipeline is here presented considering data collected from a monitoring campaign on the "Matilde donjon" in Livorno (Italy) and reporting preliminary numerical results on the identification of the modal parameters.Source: LECTURE NOTES IN CIVIL ENGINEERING, pp. 610-619. Milano, Italy, 30-08/01-09/2023
DOI: 10.1007/978-3-031-39109-5_62
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2023
Contribution to book
Restricted
From structural health monitoring to finite element modeling of heritage structures - The Medieval Towers of Lucca
Azzara Rm, Girardi M, Padovani C, Pellegrini D
This chapter describes the experiments carried out on three medieval masonry towers in the historic center of Lucca, Italy. The towers have been continuously monitored by high-sensitivity seismic stations that record the structures' response to the dynamic actions of the surrounding environment. Special attention is devoted to the Guinigi Tower, one of the most iconic monuments in Lucca, whose monitoring campaign started in 2021. The goal of the chapter is to show the effectiveness of dynamic monitoring as a valuable source of information on the structural properties of the towers and sketch the capabilities of experiment-based finite element modeling.DOI: 10.1201/9781003306924-7
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Azzara Rm, Girardi M, Padovani C, Pellegrini D
This chapter describes the experiments carried out on three medieval masonry towers in the historic center of Lucca, Italy. The towers have been continuously monitored by high-sensitivity seismic stations that record the structures' response to the dynamic actions of the surrounding environment. Special attention is devoted to the Guinigi Tower, one of the most iconic monuments in Lucca, whose monitoring campaign started in 2021. The goal of the chapter is to show the effectiveness of dynamic monitoring as a valuable source of information on the structural properties of the towers and sketch the capabilities of experiment-based finite element modeling.DOI: 10.1201/9781003306924-7
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CNR IRIS | CNR IRIS | www.taylorfrancis.com
2023
Conference article
Open Access
A digital twin-based platform for structural health monitoring: preliminary results
Girardi M, Padovani C, Pellegrini D
This paper describes the preliminary results of the REVOLUTION project, focused on designing and implementing an open-source, digital twin-based platform for the structural health monitoring of architectural buildings and infrastructures. The platform leverages several technologies, such as 2D/3D digitalization techniques, sensor networks, numerical modelling, and damage detection algorithms. Integrating such technologies will allow us to build accurate digital twins of historical buildings, monitor their dynamic properties, model their mechanical behaviour, detect damages and anomalies and plan intervention strategies.
Girardi M, Padovani C, Pellegrini D
This paper describes the preliminary results of the REVOLUTION project, focused on designing and implementing an open-source, digital twin-based platform for the structural health monitoring of architectural buildings and infrastructures. The platform leverages several technologies, such as 2D/3D digitalization techniques, sensor networks, numerical modelling, and damage detection algorithms. Integrating such technologies will allow us to build accurate digital twins of historical buildings, monitor their dynamic properties, model their mechanical behaviour, detect damages and anomalies and plan intervention strategies.
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CNR IRIS | inm.cnr.it | ISTI Repository | CNR IRIS